We're excited to announce that we have a limited number of vouchers for Google Cloud credits ($300 each) to award to deserving players. If you'd like to be considered for this award, write a response to this forum post (can be as short as you want) explaining what you would do with a $300 Google Cloud voucher for playing Halite.

Note that this is an extra $300 - Google offers $300 to new Google Cloud customers, so if you're new to Google Cloud you'll have $600 to play with.

Of course, you don't have disclose your Halite strategy in the process, but give us a high-level overview of what you would do with these resources - what kind of bot you'd make that you couldn't build without some cloud support.

We'll make some decisions about who gets vouchers by November 17th, so if you're one of the lucky ones to receive a voucher (and if you're American) you can use some of your Thanksgiving break to dive in!

Cool! I'm working on an evolutionary algorithm to select between pre-programmed strategies based on local circumstances. It's going to take a lot of iteration so extra compute would be much appreciated.

Hello! I would use the voucher credits to perform evolutionary optimization with my bot's turn-dependent variables. I would also like to perform basic analytics to determine which types of game setups my bot needs to improve on.

I am planning to train convolution neural network on my bot with an image fashion, which is a pixel level multi-channel input, considering both local receptive fields and global pooling information, I would like to generate gradient field for navigation. It is just an idea for now and it is definitely a large scale learning process that requires GPU processing. If the supervised learning results go well, I would like to push it to Reinforcement Learning to train massive amount of self-battle games.

We're attempting to create a hybrid bot by training high level strategy choosing through Neuroevolution, and implementing low level strategy execution ourselves! We've already trained a lot of bots and managed to hit rank 200 at some point. We still have a long ways to go, but being able to offload training to a Google Cloud worker would be excellent

I would work on an A3C based RL system. This requires running the game many times in parallel and then training the model on a GPU. While I am not 100% set on an architecture yet I think it makes sense to create a Docker container that downloads the latest weights of a model and then runs the game. It could push the state, action, reward pairs back to a central storage unit. Kubernetes would orchestrate the containers that run the game while a GPU instance could pull from the storage repository and continuously train the model. This kind of setup is very hard to do on local machines. In return for the free credit I'll throw in a write-up plus the code for the setup (you may tune the network yourself ). You can find some of my previous writing on RL here.

Thanks a lot for providing this great incentive! If I get the voucher I will use the extra credit to train my RNN model with more training data than before. I am currently using AWS and I am running out the 150 dollar student pack credit. It would be great to explore Google Cloud with the extra $300!

I develop from a $200 Chromebook, and have no other laptop to use for Halite. I have been using Google Cloud Compute engines for the past six months and they have been essential to my development, even beyond Halite. This extra credit would be a huge help to my personal projects, and would allow me to keep experimenting with my swarm reinforcement learning bot.Thank you!

@julskast: Last time I checked Google Cloud Platform was not available for individuals in Europe, has that situation changed? And if not is this voucher available for Europeans anyway?

I created a CNN based bot for Halite 1 that finished in Diamond (#21). My original plan was to start with a supervised learning bot that I would use as a basis for a RL bot but the training was very long on my laptop's GPU and I ran out of time, so these credits would have been very helpful.

This year's game is very different but I have found a way to turn it into a similar ML task that can leverage the use of convolutional neural networks. My approach will be similar: start with a supervised model and use it as a basis for a RL model.

Working with tensorflow on google cloud platform GPU machines is part of my daily job so I would be up and running in no time. Actually if it turns out that Google Cloud Platform is now available for individuals in Europe I will definitely use the free credit, but more credit doesn't hurt